Update from the 15th International Workshop on Co-Morbidities and Adverse Drug Reactions in HIV

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Daniel Lee, M.D., of UC San Diego Owen Clinic, presents "Update from the 15th International Workshop on Co-Morbidities and Adverse Drug Reactions in HIV"

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Update from the 15th International Workshop on Co-Morbidities and Adverse Drug Reactions in HIV

  1. 1. AIDS CLINICAL ROUNDS The UC San Diego AntiViral Research Center sponsors weekly presentations by infectious disease clinicians, physicians and researchers. The goal of these presentations is to provide the most current research, clinical practices and trends in HIV, HBV, HCV, TB and other infectious diseases of global significance. The slides from the AIDS Clinical Rounds presentation that you are about to view are intended for the educational purposes of our audience. They may not be used for other purposes without the presenter’s express permission.
  2. 2. Daniel Lee, MD Clinical Professor of Medicine UCSD Medical Center – Owen Clinic December 6th, 2013
  3. 3. BLACK BOX WARNING/DISCLAIMER This talk represents my opinion based upon my interpretation of the data and my clinical observations and experience from seeing patients in the Owen Clinic for the past 15+ years
  4. 4. Outline • Aging • Bone Disease • Cardiovascular Disease • Lipids • Bonus – 2013 ACC/AHA Guideline on Treatment of Cholesterol to Reduce ASCVD Risk
  5. 5. BRUSSELS Manneken Pis
  6. 6. AGING
  7. 7. Inflamm-ageing • Inflammaging is a multifactorial and systemic process, characterized by complex interactions • It is associated with the progressive increase of the inflammatory tone with age, fostered by “garbaging” Franceschi C. 15th IWCADR in HIV. October 2013. Plenary 1. Cevenini E, et al. Curr Opin Clin Nutr Metab Care 2013; 16: 14-20.
  8. 8. Inflamm-ageing • Inflammaging is the pathological side of a physiological phenomenon/program crucial for survival • Inflammaging is triggered by “Garbaging” • Garbaging includes a variety of “danger signals” – Exogenous (viruses, bacteria including the gut microbiota) – Endogenous (senescent cells, damaged organelles, altered/modified proteins and N-glycans, mtDNA, ATP, ROS, AGE, ceramides) • Two fundamental and unavoidable activities (ie. eating and moving) can generate danger signals – Exercise may induce inflammation Franceschi C. 15th IWCADR in HIV. October 2013. Plenary 1.
  9. 9. Gut Microbiota, Health, Disease, & Aging • Gut microbiota is required for development of immunity – Microbiota changes with age (early changes in life can increase risk for immunological diseases later in life) – Microbiota depends on diet diversity (changes in microbiota seen in institutionalized elderly vs. community-based elderly) Shanahan F. 15th IWCADR in HIV. October 2013. Plenary 2.
  10. 10. Effect of ARV Penetration into CNS on Incidence of AIDS-Defining Neurologic Conditions • Objective: to estimate the effect of the CPE score on incidence of 4 AIDS-defining neurologic conditions – HIV dementia, Toxoplasmosis, Cryptomeningitis, PML • HIV-Causal Collaboration: prospective cohort from 6 European countries and the US – ARV naïve at baseline – No history of AIDS – 55,814 individuals followed for a median of 31 months • 35,402 – low CPE (4-7), 15,089 – medium CPE (8-9), 5,323 – high CPE (10-16) Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3. CPE = CNS Penetrating Effectiveness
  11. 11. Effect of ARV Penetration into CNS on Incidence of AIDS-Defining Neurologic Conditions Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3. CPE = CNS Penetrating Effectiveness
  12. 12. Effect of ARV Penetration into CNS on Incidence of AIDS-Defining Neurologic Conditions • Conclusions – The incidence of HIV dementia (but not of other neuroAIDS conditions) increases by more than 50% after initiating an ARV regimen with a high CPE score compared with a low score • Limitations – Incomplete adherence, confounding by indication, few events, average followup <3 years, may not be generalizable to resource-limited settings or to other health care systems, diagnostic procedures reflect standard clinical practice rather than standardized research criteria Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3. CPE = CNS Penetrating Effectiveness
  13. 13. Question #1 • Is aging a normal or an abnormal process (ie. disease) of life? • 1. Normal process • 2. Abnormal process
  14. 14. Question #2 • In regards to the concept of aging, what do you think is most likely to cause aging • 1. Inflammation • 2. Genetics (accumulation of damage to DNA, telomere shortening, etc.) • 3. Mental Stress • 4. Other
  15. 15. Current State of Aging Research • Multiple theories including biological and genetic theories • Focused on evaluating the (distal) effects of aging on the development of disease – Brain (cognitive function) – Physical body (physical function) • Current thinking – for example, we can develop medications or treatments to reduce inflammation associated with aging • Does inflammation cause aging or is it just an association? Inflammation Aging or ?? Inflammation/Aging • Are we thinking too distally? • What causes aging to occur more proximally?
  16. 16. Mental Stress and Aging • Mental stress can have a proximal effect on the brain and the physical body • Mental stress (in response to external or internal stimuli) in the form of chronic negative thoughts and emotion (conscious and unconscious) may trigger a cascade of physiologic changes in the brain and body, including chronic activation of the stress response (↑cortisol/epinephrine), eventually leading to a chronically overstimulated/inflammatory state which is cumulative over one’s lifetime, and may lead to epigenetic changes, thus making a person more susceptible to disease over time
  17. 17. HIV and Aging • Many of our patients have had to deal with mental stress from an early age – Physical, mental, and/or sexual abuse by others • Many of our patients have had difficulty coping with these multiple stressors including their HIV dx – Maladaptive coping strategies to escape from pain of life • Substance abuse (illicit drugs, EtOH, prescription drugs), sexual addiction, overeating, etc. • Poor decision making – Result in cumulatively high levels of stress, anxiety, depression • Is it surprising that HIV+ age quicker than HIV-?
  18. 18. BONE DISEASE
  19. 19. ART and Loss of BMD – 1st Line ART Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  20. 20. ART and Loss of BMD – 2nd Line ART Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  21. 21. ART and Loss of BMD – Switching ART Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  22. 22. ART and Loss of BMD Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  23. 23. Pathogenesis of HIV and Low BMD Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  24. 24. Pathogenesis of HIV and Low BMD Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  25. 25. HIV Associated with High Bone Turnover • All bone turnover markers (BTM) are increased in HIV+ compared to HIV– Bone Formation • Osteocalcin • Procollagen type 1, N-terminal (P1NP) – Bone Resorption • Collagen type 1 cross-linked C-telopeptide (CTX-1) • Higher BTM correlate with lower BMD • However, differences in BTM do not explain all of the effect of HIV on BMD Cotter AG, et al. IAS 2013. Abstract MOPE077.
  26. 26. HIV, Bone Turnover and ART Initiation Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
  27. 27. ART Impact on Bone Mineral Density (BMD) • In the 2 years after ART initiation, BMD decreases by 2-6%, regardless of the ART regimen used1 • • • Similar to the 2-year decline in BMD among women age 50-59 years in the general population1 Associated with rapid increases in bone turnover markers, including markers of bone resorption (eg. CTx) and markers of bone formation (eg. OC, P1NP)3,4 Markers of bone resorption increase earlier and to a greater extent than markers of bone formation, creating a “catabolic window”4 • Some specific ART agents have independent effects on BMD with ART initiation • Tenofovir DF (TDF) has been associated with independent decreases in BMD with ART initiation and greater increases in bone turnover markers3,4 • It is unclear whether early changes in bone turnover markers predict bone loss following ART initiation in treatment-naïve patients • In the RADAR study, increases in bone turnover markers at 16 weeks were associated with decreases in total BMD (tBMD) at 48 weeks in HIV+, ARTnaïve persons initiating TDF/FTC/DRV/r or TDF/FTC/RAL5 1. Clin Infect Dis. 2010; 51:937-46. 2. Antivir Ther. 2011; 16(7):1063-72. 3. Clin Infect Dis. 2010; 51(8):963-72. 4. 18th CROI. 2011. Abstract 833. 5. IAS 2013. Abstract WEPE512. Adapted from Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
  28. 28. Changes in Bone Turnover Markers and Association with Decreased Total BMD • PROGRESS study: Randomized, open-label, multicenter trial comparing the safety, tolerability, and antiviral activity of LPV/r + RAL or LVP/r + TDF/FTC in HIV-infected ART-naïve subjects – 206 patients were randomized and received LPV/r 400/100 mg BID with RAL 400 mg BID or TDF/FTC 300/200 mg QD • Objectives: – To evaluate changes in bone turnover markers (BTM) in subjects initiating LPV/r + RAL or LPV/r + TDF/FTC • Osteocalcin (OC), Type 1 C-terminus telopeptide (CTx), Procollagen type 1 propeptide (P1NP), Bone-specific alkaline phosphatase (BSAP) – To test whether there is an association between baseline BTM levels and early changes from baseline (Wk 4 & 16), and clinically significant bone loss at Wk 96 (ie. ≥5% decline in BMD) Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17. BMD = Bone Mineral Density
  29. 29. Changes in Total BMD Through 96 Weeks in the PROGRESS Study Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17. tBMD = Total Bone Mineral Density
  30. 30. Mean (±SD) Absolute Changes from Baseline in Bone Turnover Markers Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
  31. 31. Proportion of Subjects with ≥5% Decrease from Baseline in Total BMD at Week 96 Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17. tBMD = Total Bone Mineral Density
  32. 32. Factors Associated with a ≥5% Decrease from Baseline in Total BMD at Week 96 • Baseline factors independently associated (P<0.05) with reduced incidence of a ≥5% decrease from baseline in total BMD at Week 96 were: • age <40 years • male gender • greater absolute change from baseline to Wk4 in P1NP • Baseline factors independently associated (P<0.05) with increased incidence of a ≥5% decrease from baseline in total BMD at Week 96 were: • White race • Baseline CD4+ T-cell count <200 cells/mm3 • Higher baseline CTx • Greater absolute change from baseline to Wk4 in CTx (bone resorption) • Greater absolute change from baseline to Wk16 in P1NP and OC (bone formation) Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17. tBMD = Total Bone Mineral Density
  33. 33. Changes in Bone Turnover Markers and Association with Decreased Total BMD • Conclusions – In the setting of LPV/r, TDF/FTC had a greater effect on bone turnover with ART initiation and was associated with a higher incidence of clinically significant bone loss, compared to RAL – Changes in bone turnover occurred very early after ART initiation – Early increases in bone resorption markers with ART initiation predicted clinically significant bone loss at 96 wks – Early increases in bone formation markers (4 wks) protected against clinically significant bone loss at 96 wks – Taken together, these data provide evidence supporting the hypothesis that early relative changes in markers of bone resorption and bone formation (i.e., the catabolic window) are important predictors of bone loss in HIV-infected persons initiating ART – The mechanisms underlying this effect and the specific effects of the ART components on bone turnover deserve further investigation Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17. BMD = Bone Mineral Density
  34. 34. BMD in AGEhIV Cohort Study • Objectives: – To assess the prevalence of osteopenia/osteoporosis in comparable cohorts of HIV+ and HIV- individuals, aged ≥45 years – To investigate associations between HIV and HIV-related characteristics and BMD • AGEhIV Cohort in Amsterdam – 597 HIV+ ≥45 years (Academic Medical Center, Amsterdam) - 75.2% MSM – 551 HIV- ≥45 years (STD clinic of Municipal Health Service, Amsterdam) – 2 yearly study visits, baseline measurement 2010-2012 • Demographics – several differences seen at baseline – HIV+ group had more blacks, lower body weight, slightly lower BMI, more likely to be current smokers with higher pack year history, more likely to be IDU, less physical activity than HIV- group – HIV+: median duration of HIV = 12.1 years, CD4 nadir 170, CD4 count = 570, 91.3% VL undetectable, 95% on ART, duration of ART use = 10.4 years Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18. BMD = Bone Mineral Density
  35. 35. BMD in AGEhIV Cohort Study Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18. BMD = Bone Mineral Density
  36. 36. BMD in AGEhIV Cohort Study • Results/Summary: – Prevalence of osteoporosis or low BMD for age was higher in HIV+ (14.4%) vs. HIV- (8.1%), P=0.001 – After adjustment for age, gender, menopausal status, ethnicity, DXA software changes, HIV infection remained significantly associated with lower femoral neck (-0.020 g/cm2, P=0.02) and total hip BMD (-0.030 g/cm2, P=0.001) • Upon further adjustment for body weight and smoking, HIV+ status was no longer independently associated with lower BMD in this largely MSM population – A strong interaction was observed between age and being MSM • In non-MSM, older age was associated with lower BMD • In MSM, younger MSM had lower BMD compared to older MSM and nonMSM of any age, irrespective of HIV status – This could not be explained by any differences in behavior (including drug use or Vit D) – Reduced BMD was not independently associated with TDF use Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18. BMD = Bone Mineral Density
  37. 37. Question #3 • In regards to the osteoporosis screening, what do you think is most reflective of your clinical practice • 1. I screen the majority of my patients for osteoporosis, but only above the age of 50 • 2. I screen the majority of my patients for osteoporosis regardless of age • 3. I screen patients who I feel are at risk for osteoporosis, but only if they are above the age of 50 • 4. I screen patients who I feel are at risk for osteoporosis, regardless of the age of the patient • 5. I rarely screen patients for osteoporosis • 6. Insurance issues/costs prevent me from screening
  38. 38. Recommendations for BMD Screening: HIV+ vs. HIV- Patient Populations HIV+ Patient Population1 • All postmenopausal HIV+ women (any age) • All HIV+ men ≥50 years old • Any HIV+ patient with a history of fracture HIV- Patient Population2 • Those with a history of fragility fracture • Women ≥ 65 yrs, Men ≥ 70 • Women in the menopausal transition, younger postmenopausal women, and men 50-69, who have clinical risk factors for low BMD/fracture • Adults >50 who have experienced a fracture • Adults with a condition or taking a medication associated with low bone mass or bone loss • Anyone being considered for or treated for osteoporosis 1. McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46 2. NOF. Clinician’s Guide to Prevention and Treatment of Osteoporosis. 2010
  39. 39. Clinical Approach to Managing Bone Disease in HIV (1) Initial approach HIV infected individual Assess risk factors Age Sex Weight/Height History Of Fractures Secondary causes Indications for DXA Lifestyle advice Smoking cessation Vitamin D and Calcium intake Weight bearing exercise Sun exposure < 50 years ♂ PREmenopausal ♀ AND NO history of fracture? ≥ 50 years ♂ POSTmenopausal ♀ AND/OR history of fracture? WAIT Measure BMD by DXA McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46
  40. 40. Clinical Approach to Managing Bone Disease in HIV (2) Work-up T-Score ≤ -2.5 OR fragility fracture Evaluate potential secondary causes identified in history (Table 2) Secondary cause Treatment Yes Treat secondary cause T-Score > -2.5 and ≤ -1 NO fragility fracture T-Score > -1 NO fragility fracture Consider Calculate FRAX score 10 year fracture risk (USA) ≥ 20% major osteoporotic AND/OR ≥ 3% hip No Yes Lifestyle advice Continue ART No Lifestyle advice Continue ART Consider Biphosphonate or other treatment Follow-up McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46 Monitor DXA in 1-2 years Monitor DXA in 2-5 years
  41. 41. Bruges
  42. 42. CARDIOVASCULAR DISEASE
  43. 43. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013 clinicaloptions.com/hiv D:A:D Updated Models of Global CVD Risk/Comparison With Framingham  Retrospective analysis of 32,663 HIV+ persons from 20 countries in Europe and Australia with – No CVD disease at entry to study, and – Data on CVD risk factors  1010 CVD events in 186,364.5 PY → overall rate of 5.42/1000 PY (95% CI: 5.09-5.76) Prior study – overall rate was 3.3/1000 PY – Includes MI (n = 493); stroke (n = 295); angioplasty (n = 129); bypass (n = 44); other CVD death (n = 36); carotid endarterectomy (n = 13) – 2 D:A:D models used (1 including exposure to certain ARV agents) and compared with Framingham model Friis-Møller N, et al. EACS 2013. Abstract PS1/3.
  44. 44. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013 clinicaloptions.com/hiv D:A:D HRs of CVD Risk Using 3 Models Risk Factor Unit D:A:D + ARVs D:A:D -ARVs Framingham (Males Only) Age Linear 22.0 24.0 21.4 Sex M/F 1.37 1.41 N/A Diabetes Y/N 1.96 2.08 1.78 Smoking Current Former 2.25 1.24 2.26 1.27 1.92 TC HDL-C Linear 2.58 0.61 2.98 0.59 3.08 0.39 Systolic BP Linear 4.59 4.56 6.91 7.38* Family hx CVD Y/N 1.37 1.39 CD4+ cell count 2-fold higher 0.89 0.89 ABC, current Y/N 1.47 PI, cumulative Yrs 1.05 NRTI, cumulative Yrs 1.03 Friis-Møller N, et al. EACS 2013. Abstract PS1/3. Reproduced with permission. *If treated.
  45. 45. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013 clinicaloptions.com/hiv D:A:D Summary of Key Conclusions  Classic CVD risk factors important in HIV+ pts 5-Yr CVD Risk by Age and Diabetes Status Framingham model D:A:D reduced model D:A:D full model Observed Kaplan-Meier  Risk related to current use of ABC lower than previous estimates – HR: 1.47 vs no current ABC use Estimated 5-Yr Risk, %  Framingham appears to underestimate risk compared with D:A:D models 12 10 8 6 4 2 0 Prior study – HR was 1.63 Friis-Møller N, et al. EACS 2013. Abstract PS1/3. Reproduced with permission.
  46. 46. Amsterdam
  47. 47. LIPIDS
  48. 48. Metabolic Substudy of iPrEx • iPrEx Study – international randomized, double-blind, placebo controlled trial of FTC/TDF in MSM – 2499 participants enrolled at 11 clinical sites – ITT analysis: randomization to FTC/TDF decreased HIV acquisition by 44% (P=0.005) – Plasma or intracellular drug was detected in 51% on FTC/TDF • Metabolic substudy: opt-in substudy at 7 sites in 5 cities – Target enrollment = 500 (~20% of parent study) – Assessments at study entry and q6months • Fasting lipids • DXA Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
  49. 49. No Differences in Baseline Lipids - iPrEx Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
  50. 50. Metabolic Substudy of iPrEx - Results Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
  51. 51. TG HDL Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
  52. 52. Metabolic Substudy of iPrEx • Conclusions: – In HIV-seronegative men taking FTC/TDF for PrEP, there were small but statistically significant across-the-board decreases in cholesterol – Changes were most pronounced at week 24 and tended to rebound by week 72 – Among those randomized to active drug, the changes were evident only in those with detectable drug levels – TG tended to increase over time in all groups but differences among groups were not significant – These changes could not be explained by baseline weight or changes in weight or fat or GI symptoms during treatment Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
  53. 53. STaR Study: Single Tablet Regimen Rilpivirine/Emtricitabine/Tenofovir DF Maintains NonInferiority to Efavirenz/Emtricitabine/Tenofovir DF and Has Minimal Impact on Fasting Lipids in ART-Naïve Adults Week 96 Results Calvin Cohen1, David Wohl2, Jose Arribas3, Keith Henry4, Jan van Lunzen5, Mark Bloch6, William Towner7, Edmund Wilkins8, Ramin Ebrahimi9, Danielle Porter9, Shampa De-Oertel9, Todd Fralich9, Kathy Melbourne9 1Community Research Initiative of New England, Boston, Massachusetts USA; 2University of North Carolina at Chapel Hill, Chapel Hill, North Carolina USA; 3Hospital Universitario, La Paz, Madrid, Spain; 4 HIV Program Hennepin County Medical Center, Minneapolis, Minnesota, USA; 5University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 6Holdsworth House Medical Practice, Darlinghurst, NSW Australia; 7Department of Infectious Disease Kaiser Los Angeles Medical Center, Los Angeles, California, USA; 8North Manchester General Hospital, Manchester, United Kingdom; 9Gilead Sciences, Foster City, California, USA 15th International Workshop on Co-morbidities and Adverse Drug Reactions in HIV Brussels, Belgium 15 October 2013 Clinical trial number: GS-US-264-0110 Clinical Trials.gov: NCT01309243
  54. 54. STaR Study Design Multicenter, international, randomized, open-label, Phase 3b, 96-week study n=394 ARV-naive HIV-1 RNA ≥2500 c/mL Sensitivity to EFV, FTC, RPV, TDF (N=786) Stratified by HIV RNA (≤ or >100,000 c/mL) RPV/FTC/TDF STR 1:1 n=392 EFV/FTC/TDF STR 48 Weeks Primary Endpoint Primary endpoint: Secondary endpoints: Cohen C, et al. 15th IWCADR in HIV. October 2013. Oral Presentation O6. 96 Weeks Efficacy of the 2 STRs by proportion with HIV-1 RNA <50 c/mL at Week 48 (Snapshot analysis); non-inferiority margin of 12% Safety and efficacy of the 2 STRs by proportion with HIV-1 RNA <50 c/mL at Week 96 (Snapshot analysis) Change in CD4 cell count at Weeks 48 and 96 Genotype/phenotype resistance at time of virologic failure
  55. 55. STaR Changes from Baseline at Week 96 in Fasting Lipids Change in mean from baseline, mmol/L (mg/dL) TC LDL TG HDL ■ RPV/FTC/TDF ■ EFV/FTC/TDF (+25) (+15) (+9) (+3) (+8) (+2) (+2) (-5) Mean Baseline Values, mmol/L Change in TC:HDL at Week 96, -0.2 in both arms For comparisons between groups using ANOVA: p<0.001 for TC, LDL, HDL and p=0.09 for TG 4.24 4.22 2.69 2.66 1.37 1.46 1.14 1.14 Changes to lipid lowering therapy* from baseline through Week 96: RPV/FTC/TDF 2.3%, EFV/FTC/TDF 4.1% Baseline lipid lowering therapy, n (%): RPV/FTC/TDF, 4 (1%) and EFV/FTC/TDF, 1 (0.3%) TC - total cholesterol, LDL - low-density lipoprotein, TG - triglycerides, HDL - high-density lipoprotein *Changes to lipid lowering therapy includes starting and any dose modifications of a lipid lowering therapy per the Investigator
  56. 56. STaR Conclusions • Overall, RPV/TDF/FTC was non-inferior to EFV/FTC/TDF through Week 96 for virologic suppression – Statistically significant difference favouring RPV/FTC/TDF for baseline HIV-1 RNA ≤100,000 copies/mL – Non-inferior for baseline HIV-1 RNA >100,000 copies/mL • Lipid parameter changes through Week 96 – Significant differences in mean change and categorical change in TC and LDL favoring RPV/FTC/TDF – Significant differences in mean change and categorical change in HDL favoring EFV/FTC/TDF • TC:HDL ratio change -0.2 in both arms • RPV/FTC/TDF is better tolerated than EFV/FTC/TDF – Fewer nervous system and psychiatric adverse events – Fewer discontinuations due to adverse events Cohen C, et al. 15th IWCADR in HIV. October 2013. Oral Presentation O6.
  57. 57. Question #4 • Have you heard about the new updated guidelines for starting statin therapy to reduce atherosclerotic CVD risk? • 1. Yes • 2. No
  58. 58. Question #5 • Which statement is false regarding the 2013 ACC/AHA guideline on treatment of cholesterol to reduce atherosclerotic CVD risk? • 1. HIV was not specifically addressed in the guidelines • 2. Treatment to specific LDL goals was eliminated • 3. A new risk calculator was developed • 4. At least 1 new surrogate marker (such as hs-CRP) was added to the risk calculation • 5. The risk calculator takes into account the race and sex of an individual
  59. 59. 2013 ACC/AHA Guideline on Treatment of Cholesterol to Reduce ASCVD Risk ASCVD = Atherosclerotic Cardiovascular Disease Stone NJ, et al. Circulation. doi:10.1161/01.cir.0000437738.63853.7a.
  60. 60. 2013 ACC/AHA Guideline on Treatment of Cholesterol to Reduce ASCVD Risk (2) ASCVD = Atherosclerotic Cardiovascular Disease Stone NJ, et al. Circulation. doi:10.1161/01.cir.0000437738.63853.7a.
  61. 61. 2013 10-Year/Lifetime ASCVD Risk Calculator ASCVD = Atherosclerotic Cardiovascular Disease http://www.cardiosource.org/science-and-quality/practice-guidelines-and-quality-standards/2013-prevention-guideline-tools.aspx.
  62. 62. High-, Moderate-, and Low-Intensity Statin Therapy Adapted from Bilazarian S. Theheart.org & Medscape; November 2013.
  63. 63. Implications of New 2013 ACC/AHA Guidelines to Reduce ASCVD Risk • Of 101 million people in US w/o CVD and aged 40-79 years – 33 million are expected to have a 10-year predicted risk of CVD ≥ 7.5% and high-intensity statins would be recommended – Another 13 million are expected to have a predicted risk of between 5% and 7.5% and statins should be considered • Criticisms – New risk score was developed for informing US populations – May overpredict risk – Despite a plethora of candidate emerging predictors of CV risk, the model ended up selecting risk factors known since the 1960s – HDL was selected to be in the model even though it is clearly noncausally related to CAD – Conflict of interest still remain with 8 of 15 panelists with industry ties Ioannidis JP. JAMA. 2013 Dec 2. doi:10.1001/jama.2013.284657. [Epub ahead of print]
  64. 64. Acknowledgments • Kathy Melbourne, PharmD • Clinical Care Options (clinicaloptions.com/hiv)
  65. 65. QUESTIONS?

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